The Manifestation of Incidental Findings in Different Experimental Visual Search Paradigms

Background Incidental findings are items of visual search that are potentially of significance, but were not the main object of the initial search. They have been previously widely discussed in the field of radiology. However, the underlying perceptual mechanisms of such phenomenon are still unclear. Objective The current study aims to examine incidental findings in different paradigms of visual search in order to reveal their primary perceptual aspects. Design Two behavioral visual search experiments were conducted. The mixed hybrid search task model was used in the first experiment, while the subsequent search miss effect was employed in the second experiment. The task was to find targets among distractors, according to given instructions. Stimuli material consisted of images of real-life objects that were randomly distributed across the screen for each trial. Results Accuracy and reaction time of the participants were analyzed in both experiments. Similar effects were observed for both parameters. Specific targets in the first experiment and typical targets in the second experiment were found significantly faster and more accurately in comparison to categorical and atypical targets. Moreover, this tendency did not depend on the order of target identification. Hence, the prevalence of the targets was revealed to be the primary factor in the case of incidental findings. Conclusion The study revealed the emergence of incidental findings in both experiments. Typical or specific targets were detected significantly more accurately, compared to atypical or categorical targets. Subsequent search misses were not detected, suggesting that target prevalence could be a crucial factor that is specific for incidental findings.


Introduction
Incidental ndings are items that were not the primary targets of the visual search, but nonetheless have potential value for the searcher. Initially, they were widely studied in radiology as medical artifacts, unrelated to the main diagnosis (e.g., Berbaum et al., 1990;Beigelman-Aubry, Hill, & Grenier, 2007). Finding signs of cancer while examining a patient with pneumonia might serve as an example of such ndings. However, recent work by Wolfe et al. (2017) examined the underlying mechanisms of such phenomena in visual search. e authors used a model specically designed to compare categorical and speci c searches in di erent conditions. ey suggested that incidental ndings were associated with categorical searches, while typical targets corresponded to speci c searches. Speci c search is a search for targets with a speci c identity (for example, when one searches for their own keys in a bag), and categorical search (Yang & Zelinsky, 2009) is a search for all targets from one category (for example, looking for vegetables in the store). Speci c search is simpler since it is based only on one representation of the primary target. Categorical search, however, demands more attentional resources, since there is no clear representation of targets. Experimental research supports these assumptions. A good illustration is a study by Max eld and Zelinsky, which investigated the in uence of categorical hierarchy on visual search (Max eld & Zelinsky, 2012). Within the study, searchers were primed with subordinate (e.g., dalmatian), basic (e.g., dog) or superordinate (e.g., animal) category names, which helped to guide and clarify searches. It was revealed that the guidance increased with increasing speci city of the category labels. Hence, targets classi ed by a subordinate, or narrower, category, were easier to nd. In a similar manner, it can be harder to nd less de ned targets in the case of the incidental ndings phenomenon. e searchers do not have clear representations of such items, although they constitute the general category of medical abnormalities.
Incidental ndings seem to be closely connected to the e ect of the prevalence of targets. It was shown in several studies that targets of high prevalence are typically identi ed much faster and more precisely than those of low prevalence (e.g., Hout et al., 2015). In case of incidental ndings, targets of low prevalence would correspond to less de ned categorical items. e underlying mechanism of the low-prevalence e ect is possibly based on forced-choice decisions made by searchers while performing the task. e thresholds responsible for making the decision to continue the search a er nding one target can be altered by various factors. Research shows that in the case of low-prevalence targets, the threshold for abandoning further search is signi cantly lower compared to the high-prevalence condition (Wolfe, Van Wert, 2010).
One of the main issues when it comes to identifying the real mechanisms of incidental ndings is the problem of experimental paradigms used for the investigation of the studied phenomena. It is a common practice for researchers to choose a standard paradigm, which enables the detection of a studied e ect and which has already shown its e ectiveness in previous experimental projects. However, for novel e ects of visual search, such as incidental ndings, the question arises of whether to choose one of the existing paradigms of visual search or to develop a new one. ere are experimental models used in visual search research that seem to be suitable for studying incidental ndings. Potentially, di erent paradigms could aid the study of various aspects of this phenomenon, since they have not yet been precisely de ned in terms of the underlying cognitive mechanisms. One model for research, closely linked to the hybrid search paradigm, was used by Wolfe and co-workers (Wolfe et al., 2017). e distinctive characteristic of the hybrid search paradigm is that it involves visual search from memory (e.g., Schneider & Shi rin, 1977;Wolfe, 2012). is is advantageous, since it resembles a visual search in reallife conditions. Another possible method, optimal for incidental ndings, could be a subsequent search misses (SSM) paradigm. SSM are the e ect of a signi cant decline in the accuracy of the identi cation of the second target (Adamo, Cain, & Mitro , 2013;Adamo et al., 2019;Fleck et al., 2010). Originally, SSM were referred to as "satisfaction of search" and were widely studied in radiology (e.g., Tuddenham, 1962;Berbaum et al., 1994). SSM are related to primary targets of search, as opposed to incidental ndings, and the target found second is typically very similar to the target found rst. Nevertheless, SSM resemble incidental ndings as perceptual phenomena of visual search. Both e ects can be related to the identi cation of additional targets following the detection of the rst target. erefore, the visual search errors related to them might be due to perceptual biases or resource limitations related to the processing of the rst target. is is speci cally important, since in experimental conditions both incidental ndings and SSM are studied within multiple target search paradigms. Hence, it is crucial to understand how to behaviorally dissociate between the two phenomena. ere were several studies that revealed the factors responsible for the accuracy shi in the case of the detection of the second target. Some studies illustrated that perceptually similar targets were identi ed more accurately (e.g., Gorbunova, 2017), while others showed the role of their categorical identity (Biggs et al., 2015) as more signi cant. All aspects considered, the similarity of targets may play a crucial role in the emergence of the discussed visual search e ects.
Di erent experimental paradigms allow the identi cation of various factors that lead to the emergence of speci c perceptual e ects. e traditional SSM paradigm provides very high target-distractor similarity. When targets closely resemble distractors, the overall visual search task becomes much harder (Duncan & Humphreys, 1989). erefore, the SSM errors might be due to the perceptual noise created by the distractors. On the other hand, the mixed hybrid search model includes objects from di erent categories, therefore creating a much larger perceptual variance among all items on display. Hence, target-distractor similarity may be a factor that behaviorally separates incidental ndings from SSM. However, the two paradigms also di er in terms of target prevalence representation. Wolfe and colleagues' model was created to easily manipulate the percentage of particular targets on screen. In standard SSM paradigms, this parameter is not varied. As such, a bias towards speci c targets throughout the task is not created. Rather, the emphasis is put on the bias created by the initially identi ed target in each individual experimental trial. is di erence might be crucial in di erentiating incidental ndings from SSM. If target prevalence is manipulated in both experimental paradigms, the results could specify the perceptual underlying mechanisms of these phenomena. e objective of this research was to study incidental ndings using two di erent experimental visual search paradigms: a mixed hybrid search model developed by Wolfe and colleagues, and an SSM paradigm. e mixed hybrid model involves searching for several targets from memory, some of which are de ned by category, while others are speci c. e procedure is separated into several blocks, so that targets and distractors are de ned for each individual block separately. In contrast, the SSM paradigm involves searching for initially de ned targets during the whole procedure. Target prevalence was chosen to be manipulated in both experimental paradigms in order to reveal its speci city to incidental ndings. e main criterion for identifying incidental ndings was the absence of statistical di erences between conditions with one target (categorical or non-typical) and two targets, as suggested by Wolfe et al. (2017). erefore, if incidental ndings emerge in both experimental models, it suggests that target prevalence is indeed the crucial factor for distinguishing the described perceptual phenomena. However, if SSM were to be found in the paradigm for SSM research, it would mean that target prevalence is not speci c for incidental ndings, and there are likely other perceptual factors that play a signicant role.

Participants
ere were originally 17 participants in this experiment. e sample size was based on the experimental work by Wolfe et al. (2017), who originally introduced the mixed hybrid search model. Slightly more participants were invited, in order to compensate for distant data collection. All were required to have normal or corrected to normal vision and to have no neurological or psychological problems. Every participant read and signed the informed consent. Data from 3 participants were excluded from further analysis, due to misunderstanding of the instructions. erefore, the nal sample consisted of 12 females and 2 males, their ages ranging from 18 to 36 years old (M = 24.14, SD = 5.14).

Stimuli material
Eight categories of food were chosen as stimuli material: vegetables, fruit, groceries, drinks, meat products, dairy products, bakery, and desserts. For each of those categories, ten di erent objects were chosen as stimuli. e images were taken from open stock-images bases and modi ed in Adobe Photoshop to isolate the objects from the background and change the image size. e stimuli represented real life objects in order to correspond to the experimental task, so primary perceptual factors like color and brightness were not speci cally controlled. However, since di erent stimuli were randomly distributed across trials, possible systematic biases related to such factors were eliminated. Each image was 160x120 pixels in size, vertically oriented. Stimuli were presented on a plain white background. ere were also two additional buttons "NO" and "OK" for reporting the absence of the targets.
Overall, six experiments were created with the following conditions: one speci c target (36% of tasks), two speci c targets (16% of tasks), one categorical target (9% of tasks), two categorical targets (1% of tasks), both speci c and categorical targets in the same task (8% of tasks) and no targets (30% of tasks). e percentage distribution is similar to that in experiments by Wolfe et al. (2017). ese conditions were then distributed among three experimental blocks: speci c, categorical, and mixed. e blocks di ered in the type of search, which was speci ed in the instructions. Within a speci c block particular objects would be searched for, in a categorical block the search would be for all objects from a given category, and a mixed block was a combination of those two types of search. e mixed block was critical in this experiment, since it implied both speci c and not clearly de ned targets, representing incidental ndings. e stimuli were distributed randomly across the screen (1248x640 pixels) within a 5 by 5 invisible grid. Participants could move along up to 55 pixels horizontally and up to 4 pixels vertically randomly from the centers of the cells in each trial. Overall, there could be 4, 8, or 12 stimuli in each individual trial, the number of targets varied from 0 to 2.

Procedure
e experiment was conducted remotely on the participants' computers. ey could use any computer with any monitor, but they were speci cally required not to use a smartphone or tablet. e participants were sent all the necessary materials, including video-instructions and the experiment les. Before running the experiment, the participants were asked to look through the list containing all the images of stimuli in order to familiarize themselves with which object belonged to which category. A er that they were asked to begin the experiment in quiet, comfortable conditions. ey were also required to use a computer mouse and a space bar during the experiment.
When the participants ran the experiment, instructions describing the task appeared. It was stated that the task resembled a "grocery shopping" task, and the participants would need to nd objects, based either on their speci c labels or the name of the category. e labels appeared before the start of each experimental block. e objective was to remember objects or category names and then search for the targets as quickly as possible. As soon as the target was found, it needed to be clicked on using a computer mouse. e buttons "OK" and "NO" served for reporting the absence of targets in conditions with only one or no targets. A er the end of each task, the participants could rest if necessary and begin the new task by pressing the spacebar.
Each speci c, categorical, and mixed block was evenly divided into two blocks, making six separate blocks. e participants had a chance to rest in between the blocks and begin a new one by pressing the spacebar. Before each block, four labels of objects or category names appeared for 12 seconds. In the speci c block there were four labels of speci c objects, in the categorical block there were four names of di erent categories, while in the mixed blocks there were two speci c labels and two category names. e labels and category names for each block were chosen at random. e order of the tasks within each block was random. Following the initial instructions, there was a training block consisting of 20 trial tasks to enable the participants to practice and contact the experimenter if anything was unclear. Next, the main part of the experiment began. is consisted of 820 tasks in total.

Results
Accuracy and reaction time for both mouse clicks were analyzed. e condition with no targets was excluded from the analysis, since it was used as a control to determine the participants' attention to a given instruction and did contain any relevant data. Accuracy and reaction time were analyzed for conditions with one speci c target, one categorical target, two speci c targets, two categorical targets, and the condition with both types of targets present together. Moreover, these conditions were analyzed separately for each experimental block: speci c, categorical, and mixed. It was necessary to examine the errors, depending on the type of search. e error analysis was carried out for di erent experimental conditions. For experiments with no targets, the accuracy and reaction time were calculated using the times when participants successfully clicked the "NO" button twice. For experiments with one speci c or categorical target, the accuracy and reaction time were calculated using times when the click on the target was followed by a click on "OK" button. For experiments with two speci c or categorical targets, the accuracy and reaction time were measured for the second target, regardless of the order in which the targets were clicked. For the experiments with both target types (in the mixed block), the accuracy and reaction time were calculated for the categorically de ned target, but only if it was found a er the speci c one. Accuracy and reaction time then were compared for the relevant experimental conditions. Reaction time was analyzed for correct response trials. Reaction times (RTs) greater than M+2SD and less than M-2SD were excluded from further analysis.
IBM SPSS Statistics v. 22.0.0.0 was used for data analysis. In order to determine which type of search (speci c or categorical) was more accurate, two-way ANOVA was used. Moreover, multiple paired sample t-tests were applied for pairwise comparisons of di erent conditions with Bonferroni adjustments. For analyzing the e ects within the mixed block repeated measures, ANOVA and pairwise comparisons with Bonferroni-Holm adjustment were used. e Greenhouse-Geisser corrections were applied when Mauchly's sphericity tests were signi cant.
Incidental ndings were detected based on the accuracy parameter. If there were no signi cant di erences between dual-and single-target tasks, incidental ndings would be detected. Otherwise, in the case of the signi cant decrease in accuracy related to dual-target trials, SSM would be detected. e reaction time parameter was considered secondary to the accuracy parameter. It was used to further clarify the di erences between di erent experimental conditions, particularly between categorical and speci c visual search.

Accuracy
Two-way ANOVA revealed a signi cant e ect of the target type factor (F(1,13) = 30.314, p < .001, η p 2 = 0.7) and the number of targets factor F(1,13) = 10.013, p = .007, η p 2 = 0.435). e factor interaction was insigni cant (F(1,13) = 2.083, p = .173, η p 2 = 0.138). e search for speci c targets was more accurate in conditions with one target (t(13) = 6.661, p < .001, d = 1.31) and two targets (t(13) = 3.144, p = .016, d = 2.91). e participants were signi cantly more accurate in detecting the only target in a task compared to two targets, but only in the speci c block (t(13) = 3.267, p = .018, d = 5.23). e accuracy did not di er signi cantly depending on the number of targets (t(13) = 0.852, p = .409, d = 0.14). e results are presented in Figure 1. Bonferroni adjustments revealed signi cant di erences between the following conditions: one speci c target and one categorical target (p < .001), one speci c target and both speci c and categorical targets in the same trial (p < .001), one categorical target and two speci c targets (p = .001), and two speci c targets and both speci c and categorical targets in the same trial (p < .001). e results are presented in Figure 2.
e results are presented in Figure 4.

Reaction time (second click)
Two-way ANOVA revealed a signi cant e ect of the target type factor (F(1,13) = 17.556, p = .001, η p 2 = 0.575) and the number of targets factor (F(1,13) = 34.542, p < .001, η p 2 = 0.727). Moreover, the e ect of factor interaction detected was signi cant (F(1,13) = 26.36, p < .001, η p 2 = 0.67). Due to this signi cant interaction, an additional one-way ANOVA was conducted separately for speci c and categorical targets (the factor being the number of targets), and another for one target and two targets conditions (the factor being target type). e additional one-way ANOVA revealed the signi cant e ect of the number of targets for speci c (F(1,13) = 45.394, p < .001, η p 2 = 0.777) but not categorical targets (F(1,13)= 4159.197, p = .469, η 2 = 0.041). Hence, the participants were signi cantly quicker to nd the second speci c target than to report the absence of the second speci c target (p < .001). However, such a pattern was not found for categorical targets. In this case, it took a statistically similar amount of time to report the second target as it did its absence (p = .469). Regarding the e ect of target type, it was signi сant for conditions with two targets (F(1,13) = 35.525, p < .001, η 2 = 0.732) and insignicant for conditions with only one target (F(1,13) = 1.112, p < .311, η 2 = 0.079). e participants were signi cantly quicker to click on the second speci c target than the categorical one (p < .001), but they tended to require an equal amount of time to report the absence of the second target, whether speci c or categorical (p = .311). e results are illustrated in Figure 5.
In the mixed block repeated measures, ANOVA revealed a signi cant e ect of the condition factor: F(2,24) = 26.323; p < .001; η p 2 = .669. Pairwise comparisons with Bonferroni adjustments revealed signi cant di erences between the following conditions: one speci c target and two speci c targets (p <.001), one categorical target and two speci c targets (p = .001), and two speci c and both speci c and categorical targets in the same task (p < .001). e results are illustrated in Figure 6.

Discussion
e results of the accuracy analysis within speci c and categorical blocks illustrate that the search for categorically de ned targets was signi cantly more prone to errors. e accuracy in detecting speci c targets was higher for experiments with both with one and two targets. is is similar to the ndings obtained in the research by Wolfe and colleagues, where error rates were signi cantly higher for categorical targets (Wolfe et al., 2017). e ndings are supported by the perceptual set hypothesis, since speci c objects are better represented in the working memory, and visual attention is guided towards them (Kristjánsson & Campana, 2010). Categorical targets are less precisely de ned, therefore the search for such items is less e cient. Similar results were reported in the study by Max eld and Zelinsky, where the e ects of the category level were studied and it was found that the less de ned the target, the lower the accuracy (Max eld & Zelinsky, 2012). As well as that, there was the e ect of SSM for the speci c block only: the accuracy declined signi cantly for the condition with two targets compared with the condition with one target. However, this was not the case for the categorical block: there were no statistically signi cant di erences between the corresponding conditions. is may be explained by the overall di culty of categorical search, particularly because the participants were accurate in no more than 60% of the trials.
Within the mixed block, there were no signi cant di erences between the experiments with both speci c and categorical targets and the experiments with only one categorical target. is nding implies that, by de nition, no SSM were observed in this block. It also corresponds to the results of Wolfe and colleagues' experiment (Wolfe et al., 2017). is is interesting since incidental ndings were indeed separated from other visual search phenomena in their study. Furthermore, in the mixed block, as in the other blocks, the search for one speci c target was signi cantly more accurate than the search for one categorical target. Furthermore, the accuracy in the experiments with one categorical target was far lower than the accuracy in experiments with two speci c targets. Hence, categorical search seems to be far less precise than speci c search.
e results of the rst click reaction time analysis further clarify the di erences between categorical and speci c search. e identi cation of a speci c target was signi cantly quicker in tasks with both one and two targets in speci c and categorical blocks. e same e ect was observed in the mixed block experiments with one speci c and one categorical target. ese ndings, once again, resemble those reported in papers by Wolfe (Wolfe et al., 2017) and Max eld (Max eld & Zelinsky, 2012). Hence, it can be assumed that nding a categorically de ned target takes more time than a speci c one. e participants were also signi cantly quicker to nd the rst target in tasks with two targets compared to tasks with one target. is suggests that, statistically, it takes less time to nd at least one out of two present targets, rather than to nd the only present target. is is typical for visual search experiments, as supported by previous experiments and known data (e.g. Kwak, Dagenbach, & Egeth, 1991;Moraglia, 1989).
With regards to the reaction time of the second click for speci c and categorical blocks, it took signi cantly less time to detect the second target if it was speci c. Moreover, it took signi cantly less time to nd the second speci c target compared to reporting its absence. is was true for both speci c and mixed conditions. is nding illustrates the higher probability of detecting the second present target before searching through all present distractors. However, in the categorical block, there were no signi cant di erences between the mentioned conditions. It took a statistically similar amount of time to detect either the second target or report its absence. A possible explanation for this nding is that the time required to make a decision is increased, whether the observed item is a target or not, due to poorly de ned target representation. As previously discussed, in the case of speci c targets such decisions are made quicker, due to both attentional guidance and distinct perceptual representations of targets. Furthermore, the reaction time for tasks with one target was not signi cantly di erent between all three experimental blocks. is is a typical nding since set sizes were evenly distributed among the various experimental conditions, meaning it would take the same amount of time to report the absence of the second target.

Participants
ere were originally 24 participants in this experiment. e sample size was based on previous experimental research on SSM (e.g., Gorbunova, 2017). All the participants con rmed via Google forms (https://www.google.com/forms/about/) that they had normal or corrected to normal vision and did not have any neurological or psychological problems. Data from one participant were excluded from further analysis, due to misunderstanding of the instructions. erefore, there were 21 females and 2 males. eir ages ranged from 19 to 34 years old (M = 22.22,SD = 4.13). e participants were given 100 rubles each for participating in the experiment.

Stimuli
Food images were used as targets and distractors belonged to several categories: cars, furniture, hats, musical instruments, and shoes. Fruits and vegetables corresponded to typical targets, while spices corresponded to non-typical targets. ere were ve objects chosen for each category and 60 images in total. e images were taken from open stock-images bases and modi ed in Adobe Photoshop to isolate the objects from the background and change the image size. Each image was 140x100 pixels in size, vertically oriented. Stimuli were presented on a plain white background. ere were also two additional buttons made for participants' answers, they contained the words "NO" and "OK" correspondingly. e salience of the two types of targets was varied. Fruits and vegetables were used as typical targets, while spices were non-typical targets. ere were ve experimental conditions: two typical targets (18% of tasks), one typical target (37% of tasks), no targets (30% of tasks), one non-typical target (5% of tasks), and both typical and non-typical tasks (10% of tasks). e stimuli were distributed randomly across the screen (1248x640 pixels) within a 5 by 5 invisible grid. ere could be 12, 16, or 20 stimuli in each individual trial. e number of targets could be 0, 1, or 2.
Procedure e experiment was conducted online using Pavlovia so ware (https://pavlovia. org/). e participants used their personal computers and were required not to use smartphones or tablets. ey were instructed to search for food among objects from other categories. e participants were informed that they could nd 0, 1, or 2 targets in each individual task. ey were asked to perform the task as quickly as possible.
ey used a computer mouse to click on targets and the buttons at the bottom of the screen in order to report the presence or absence of targets, similar to Experiment 1.
A er the end of each task, the participants could rest if necessary and begin the next task by pressing the spacebar. e rst 60 tasks did not contain non-typical targets, and the order of presentation in the following trials was randomized among all ve experimental conditions. ere were 495 tasks in the main block of the experiment.

Results
e analysis was the same as for the mixed block in Experiment 1.

Accuracy
Repeated measures ANOVA revealed the signi cant impact of the experimental condition factor: F(2,50) = 10.671; p < .001; η p 2 = 0.327. Pairwise comparisons with Bonferroni-Holm adjustments revealed signi cant di erences between the following conditions: one typical and one non-typical target (p < .001), one typical target and both typical and non-typical targets in the same task (p = .015), two typical targets and one non-typical target (p = .009), and two typical targets and both typical and non-typical targets in the same task (p = .035). e results are presented in Figure 7.

Reaction time ( rst click)
Repeated measures ANOVA revealed the signi cant impact of the experimental condition factor: F(2,50) = 144.546; p < .001; η p 2 = 0.868. Pairwise comparisons with Bonferroni-Holm adjustments revealed signi cant di erences between the following conditions: one typical target and two typical targets (p < .001), one typical target and one non-typical target (p < .001), one typical and both typical and non-typical targets in the same task (p < .001), two typical and one non-typical target (p < .001), two typical and both typical and non-typical targets in the same task (p = .015), and one nontypical target and both typical and non-typical targets in the same task (p < .001). e results are presented in Figure 8.

Reaction time (second click)
Repeated measures ANOVA revealed the signi cant impact of the condition factor: F(1,27) = 47.033; p < .001; η p 2 = 0.681. Pairwise comparisons with Bonferroni-Holm adjustments revealed signi cant di erences between the following conditions: one typical target and two typical targets (p < .001), one typical and both typical and non-typical targets in the same task (p < .001), two typical and one non-typical target (p < .001),two typical and both typical and non-typical targets in the same task (p < .001), and one non-typical target and both typical and non-typical targets in the same task (p < .001). e results are presented in Figure 9.

Discussion
ere were no signi cant di erences in accuracy between the baseline experimental condition with one non-typical target and the crucial experimental condition with both typical and non-typical targets in the same task. erefore, no SSM errors were observed, as in Experiment 1. Interestingly, SSM errors were also not detected for tasks with only typical targets. is can be explained by the e ect of high target prevalence (Hout et al., 2015). It is important to note that the targets and distractors belonged to di erent categories. erefore, the target-distractor similarity was not large. is could be the major factor leading to the overall reduction of task di culty, as it is easier to nd targets when they are perceptually di erent from the distractors (Duncan & Humphreys, 1989). In this case, targets were also categorically di erent, which made the guidance of visual search even easier. As expected, the results for the reaction time showed that it took signi cantly less time to identify typical targets in comparison to non-typical ones. is further supports the assumption that typicality plays a signi cant role in the e ectiveness of visual search, as typical targets have better representations in working memory. is e ect was also observed for non-typical targets that were found a er typical ones. In compliance with the categorical perception hypothesis, the search becomes guided by the speci c characteristics of the initially found target (e.g., Kristjánsson & Campana, 2010). Finally, the participants were signi cantly quicker to nd the rst target in the case of two in-trial present targets, as well as to report the second present target in comparison to reporting its absence. ese ndings were the same as in Experiment 1.

General discussion
Two visual search paradigms provided di erent ways of studying the same phenomenon. Incidental ndings are de ned as targets that do not relate to the primary search goals but are of potential interest to the searcher. e criterion for distinction between incidental ndings and the similar e ect of subsequent search misses (SSM) was the di erence in accuracy between single-and dual-target tasks. Incidental ndings can be identi ed only in the absence of such statistical di erences. e main nding of Experiment 1 was the di erence between categorical and speci c visual search for targets. Categorically de ned targets were easier to miss. As initially suggested by Wolfe and colleagues (Wolfe et. al., 2017), incidental ndings are most closely associated with such targets. Targets that have clear representations are typically found rst, so less attentional resources are le for potentially remaining ones. Signi cantly, there was no decrease in accuracy for nding the second target a er the rst one. is distinguishes this e ect from previously described SSM. Hence, accuracy in this case does not simply depend on the order in which the targets are identi ed, but rather on the search characteristics themselves. Similarly, no SSM were detected in Experiment 2, although the standard SSM experimental paradigm was used. Notably, though, the search was categorical in this experiment, and the targets di ered in typicality. It was shown that the search for typical targets was signi cantly more accurate, alike to the search for speci c targets in Experiment 1. Taking both ndings into consideration, it seems that the major factor is the prevalence e ect of the targets. In both experiments, high-prevalence items were found much more e ciently than low-prevalence targets. In both experimental and real-life situations, targets that have the most priority are more likely to be found. is might be one of the most important features of the incidental ndings phenomena.
It is signi cant to note that the results in both experiments ultimately illustrated very similar tendencies, although target-distractor similarity was di ered signicantly. While in Experiment 2, targets belonged to a completely separate category in relation to distractors, items in Experiment 1 all constituted one category. It would seem, therefore, that the search in the second experiment would be far easier for the participants. However, this did not seem to play such a signi cant role. Firstly, the hybrid search paradigm in the rst experiment is generally harder, since it involves searching from memory. Secondly, irrespective of task di culty, the ndings represented no signi cant decline in accuracy for nding the second target. Finally, despite the seeming target-distractor similarity distinction in the two experiments, the crucial point might be not categorical, but based on perceptual di erences of the stimuli. Even though all items belonged to the same category of food in Experiment 1, they were very di erent perceptually. ese characteristics could potentially be more important, since in real life the search task demands nding items with speci c visual features. Such features may prevail over unclear categorical representations and, thus, guide the search for targets. However, there are data suggesting the overall categorical superiority in relation to perceptual phenomena in visual search (e.g., Biggs et. al., 2015). At the same time, this point needs further clari cation, particularly with regards to incidental ndings. Hence, a potential continuation of this study might be to vary the target-distractor similarity within one experiment in order to reveal the role of this particular factor.
Overall, the study revealed that incidental ndings di er from SSM. is e ect relates speci cally to categorical visual search -a search de ned by the category of objects. Additionally, prevalence of the targets plays an important role, since incidental ndings relate to less common and less represented targets. ese factors should be addressed by the optimal paradigm for studying incidental ndings as a separate visual search phenomenon. Regarding the factor of target-distractor similarity, incidental ndings seem to be perceptually di erent from the main targets of search. However, the speci c role of perceptual di erences should be clari ed in further research.
Conclusion e purpose of this research was to study incidental ndings in two separate experimental paradigms of visual search in order to reveal the primary factors speci c to this phenomenon. e mixed hybrid search model and subsequent search misses (SSM) paradigm were used in two behavioral visual search experiments. e results revealed similar patterns in terms of participants' accuracy and reaction time. e most signi cant factor for incidental ndings was concluded to be the target prevalence e ect. Targets that were more typically found seemed to create a certain bias towards similar items. However, rare targets that were more categorically distant from the initially identi ed target were more likely to be missed by the searcher. ese results seem to be speci c to incidental ndings as opposed to SSM. Overall, the ndings provide additional information about incidental ndings as a separate visual search phenomenon.

Limitations
Both experiments were conducted online due to the COVID-19 pandemic situation, which means that quite a few parameters of the experimental study could not be controlled. ose include the technical characteristics of the computers that varied from one participant to another, the conditions of noise and lighting, and others. Moreover, the display size was signi cantly reduced, since the majority of the participants had laptops with rather small screens. is implied a higher density of the stimuli on screen. In the case of visual search experiments, this might be an issue as it tends to make the task easier for the participants. However, since both experiments were very similar in technical aspects (e.g., stimuli size, grid parameters), it was possible to adequately compare the results. Moreover, since the critical parameter in both experiments was accuracy, rather than reaction time, and the results illustrated typical behavioral patterns for the described e ects, the di erences in technical parameters do not seem to have drastically in uenced the data. As well as this, it has been argued that web-based experiments are appropriate for collecting such parameters as reaction time, even though they traditionally seem to be quite estimation-sensitive (Chetverikov & Upravitelev, 2015).

Ethics Statement
All experiments reported in this manuscript were carried out in accordance with the Declaration of Helsinki and the existing Russian and international regulations concerning ethics in research. All participants provided written informed consent. We did not seek approval by an institutional review board for the experiments because it is not required for a study of the type reported in this manuscript.

Author Contributions
O.R.: originator of the concept, experimental planning, programming, data collection, data analysis, discussion of the results, manuscript preparation. E.G.: originator of the concept, experimental planning, discussion of the results, manuscript preparation.

Con ict of Interest
e authors declare no con ict of interest. Wolfe, J.M., Soce, A.A., & Schill, H.M. (2017). How did I miss that? Developing mixed hybrid visual search as a "model system" for incidental nding errors in radiology.